The present invention is in the field of frequency correction of receive signals, as e.g. occurring as Doppler shifts in spread spectrum received signals when there is a motion between a transmitter and a receiver.
In wireless communications it is a known problem that frequency shifts occur, if receiver and transmitter are not stationary. The so-called Doppler shifts are a general problem of mobile communications, as receivers of frequency shifted signals often need to apply frequency corrections in order to achieve sufficient signal quality. This problem has a general character and occurs in basically most of mobile communication systems. In the following, reference will be made to spread spectrum communication systems, however, similar considerations can be taken with respect to other mobile communication systems as well.
In spread spectrum communication systems, predefined sequences, so-called chip sequences, are utilized in order to spread an information signal in the frequency domain. At a receiver, a replica of said chip sequence is generated, in order to correlate the generated sequence with the receive or received signal. In the following the expressions of receive and received signal will be used synonymously. Through correlation, the desired signal can be extracted from the receive signal, this operation is also referred to as despreading. The utilized chip sequences are also known as PRN codes (PRN=Pseudo Random Noise). The correlation at the receiver can wipe out the PRN code and is basically done by correlation, i.e. by multiplying and integrating the incoming signal with the code replica.
In order to enable proper correlation, the beginnings of both codes, i.e. the replica and the code within the received signal, should be aligned in time, which can be done by an iterative search through correlations with received signals of different time shifts. So in a first dimension a proper time shift can be evaluated.
Another dimension of search can be frequency, where signal errors or distortions are due to the so-called Doppler effects. Due to the mutual motion of the transmitter and receiver, the received signal can be shifted in frequency. Therefore, the second search dimension may be in frequency. Both effects, frequency and time shifts, are unknown at the receiver, and different algorithms can be used to decrease them.
Finding the delay of the incoming code, also referred to as the code delay, is the aim of for example GNSS (GNSS=Global Navigation Satellite Systems). A correlation in the frequency domain, for example utilizing the FFT (FFT=Fast Fourier Transform), can be used to determine this value. As mentioned above, care also needs be taken on the Doppler effect, as the frequency shift should be deleted or decreased as well. In order to do so, one known algorithm is to perform an iterative search through a grid of possible Doppler frequencies, which is determined by the Doppler frequency range, which can for example be [−5, 5] kHz in a GNSS with static receivers.
Moreover, there are known algorithms for increasing a signal-to-noise-ratio (SNR) of a correlation value at the receiver. In the following correlation of receive signal segments with chip sequences will be illuminated.
Here and for the remainder a correlation value shall correspond to a result of correlating two sequences, which yields a correlation function or sequence composed of multiple correlation values. However, within these resulting sequences there may be particular correlation values, e.g. a peak value or a value fulfilling a predetermined condition which is to be detected for example to find a correct delay of a received sequence. Therefore the expression of correlation value may correspond to a value of a correlation result in terms of a sequence or function.
An actual public algorithm for increasing the SNR is for example the so-called alternate half-bit method (AHBM) and the so-called full-bit method (FBM). They defer with respect to the coherent integration time, which is used at a correlator for integration, and which is half of a bit (AHBM) or a full-bit (FBM) duration respectively. Integration times which exceed those durations, refer to incoherent integrations, because outside these durations the modulating data is unknown, therefore coherent superposition of these signal parts may not be anticipated. However, it is also known that the gain of incoherent integration is not as high as the gain of coherent integration, especially in low SNR scenarios. For example in indoor scenarios, where rather weak receive signals can be received, with a short coherent integration time proper detection may not be possible. A problem of these conventional systems is that a proper positioning within indoor scenarios or low SNR scenarios is difficult.
Furthermore, the amount of coherently integrated signal duration limits the grid side of a Doppler frequency grid to be searched. The maximum frequency jump, which can be done, is given by the expression
                              Δ          ⁢                                          ⁢                      f            bin                          =                              2                          3              ·                              T                COH                                              .                                    (        1        )            
This condition takes into account, that phase variations within a coherently integrated signal fraction (of duration TCOH) should be limited in order to prevent destructive superposition. If one demands that at least half of the signal power can be integrated within the coherent time, it yields that the maximum allowable phase shift is two-thirds of π, implying the above condition for the maximum frequency jump.
For example, in indoor scenarios, it is already known that the SNR is very low. Therefore, it seems to be appropriate to increase the coherent integration time in order to acquire s satellite's signal properly and for afterwards obtaining the users position more properly as well. However, according to the above condition, the higher the coherent integration time the finer the Doppler frequency grid, and consequently, the higher the complexity since a finer Doppler grid provides a lot more Doppler frequencies to be considered. Moreover, when extending coherent integration times to a higher value than a single bit duration, this implies that the data symbols or bits within the coherent integration time should be known to be able to combine them coherently. Otherwise if the bits are unknown and integrating across bit boundaries of different bits, bit sign changes can cause destructive superposition. This again would imply that a pilot channel has to be available in the communication system, i.e. a known transmit data sequence. If the transmitted bit sequence is not known, and noting that one bit translates at least one chip sequence or a number of chip sequences which could be combined coherently, the receiver does not know whether a sign change has occurred or not at the bit boundaries. Therefore, coherent combining across bit borders is very critical if the bits are unknown.
As already mentioned above, increasing the coherent integration time generates a proportional increment of the number of correlations to be performed, assuming that at least one correlation needs to be performed per Doppler frequency shift conceivable. Moreover, even if a system has a pilot channel the pilot channel consisting of a repeating data sequence would then imply that a synchronization process has to be carried out, which can dramatically enlarge the complexity of a detection algorithm in terms of the amount of operations that need to be carried out.
The abovementioned AHBM and FBM algorithms have only a limited coherent integration time, due to the bit boundaries and therefore their performance is very limited with respect to low SNR scenarios. For longer coherent integration times a pilot channel is necessitated, but even if there is a pilot channel, the number of operations that have to be performed with the pilot channel may take a lot of processing time at the receiver. If such synchronization is necessitated a receiver structure may become more complex, its power consumption may rise and the complexity of the detection algorithm may increase significantly.
WO 006/119816a1 describes a concept for decoding a signal based on an incoming stream of data samples representing at least one downconverted digitized spread spectrum source signal. The received data samples are subdivided into a number of data blocks, which are individually correlated with a locally available code replica, before being processed for Doppler frequency compensation.
US 2007/0025476 A1 discloses methods and apparatus for determining carrier frequency errors of a serial offset quadrature pulse shaped signal, such as a minimum shift keyed signal. The carrier frequency error is determined by receiving a quadrature pulse shaped signal having a synchronization sequence detecting synchronization of the quadrature pulse shaped signal and storing a baseband inphase signal and a baseband quadrature signal of the synchronization sequence while detecting synchronization. After detecting synchronization segments of the stored baseband inphase and quadrature signals are read and correlated with the spreading sequence. Carrier frequency error is then estimated based on phase differences between each of the correlated signals.
U.S. Pat. No. 6,195,328 B1 provides an improved acquisition and tracking system for GPS signals. The system relies on block adjustment of the synchronizing signal of the bi-phase shift keying signal in order to obtain correct carrier frequency and phase angle. This improved system has the advantages of being more robust in the presence of noise than conventional approaches and also of lending itself to simplified implementation since synchronization of the coarse/acquisition code need only be within half of a chip in order to maintain lock.